Aquatic ecological carrying capacity is an effective method for analyzing sustainable development in regional water management. In this paper, an integrated approach is employed for assessing the aquatic ecological carrying capacity of Wujin District in the Tai Lake Basin, China. An indicator system is established considering social and economic development as well as ecological resilience perspectives. While calculating the ecological index, the normalized difference vegetation index (NDVI) is extracted from Moderate Resolution Imaging Spectroradiometer (MODIS) time-series images, followed by spatial and temporal analysis of vegetation cover. Finally, multi-index assessment of aquatic ecological carrying capacity is carried out for the period 2000 to 2008, including both static and dynamic variables. The results reveal that aquatic ecological carrying capacity presents a slight upward trend in the past decade and the intensity of human activities still exceeded the aquatic ecological carrying capacity in 2008. In terms of human activities, population has decreased, GDP has quadrupled, and fertilizer application and industrial wastewater discharge have declined greatly in the past decade. The indicators representing aquatic ecosystem conditions have the lowest scores, which are primarily attributed to the water eutrophication problem. Yet the terrestrial ecosystem is assessed to be in better condition since topographic backgrounds and landscape diversity are at higher levels. Based on the work carried out, it is suggested that pollutant emission be controlled to improve water quality and agricultural development around Ge Lake (the largest lake in Wujin District) be reduced.

Disease maps and forecasts developed using satellite remote sensing data can inform public health decisions and improve disease control and epidemic response. The open-source, client-based software Epidemiological Applications of Spatial Technologies (EASTWeb) was developed to automate the retrieval, processing, and storage of satellite remote sensing data for public health research and applications. To improve the system, there is a need to expand the types of earth observation data that EASTWeb can process so that it can be used more broadly in a wide range of geospatial health applications. The EASTWeb framework introduces novel plugins and a plugin factory to provide users a convenient way to customize the framework into applications for different earth science data streams. This paper briefly reviews the EASTWeb system, upon which the EASTWeb framework is built. It presents the details on the design of the top level plugin framework and its four sub-frameworks, and a scheduler that controls the working threads.